This paper reviews literature on dynamic analysis and intelligent control techniques for flexible robot manipulators. First, a comparative dynamic analysis of flexible manipulators was presented and then control strategies were categorized and studied. Fuzzy logic, neural network, and genetic algorithm approaches were introduced and a range of contributions of such methods in flexible robot control were presented. A total of 115 papers were surveyed in this research, covering a sufficient depth in assessment of dynamic and control of flexible manipulator systems for the time span of 1970–2013.

Proportional integral derivative (PID) regulators are the most practical control schemes for industrial wind turbines. The key to PID design is the determination of the control parameter gains, which motivated our attempts to construct an adaptive PID control for wind turbines allowing auto-tuning of the gains without the need for trial and error processes. By equipping a novel PID-based fault-tolerant controller with a Nussbaum-type function, a robust adaptive and fault-tolerant control scheme is developed for wind turbines. Compared with available methods, the proposed controller has advantages, such as the ability for dealing with complete nonlinear dynamics of wind turbines, including model uncertainty, ability to ensure system stability by using an adaptive self-tuning gain algorithm, and robustness against wind speed variation. Furthermore, it has the ability to accommodate unexpected actuator faults and the accommodation of an unknown control direction. However, the salient feature of the proposed controller lies in its simple structure and inexpensive online computational demands while dealing with the nonlinear dynamics of wind turbines and unknown disturbances. It is shown that the proposed pitch angle controller remains continuous and smooth and all the closed-loop system signals are guaranteed to be uniformly ultimately bounded. Theoretical analysis and numerical simulations are presented to confirm the effectiveness of the proposed control strategy.